Financial Services
Intelligent Automation in Financial Crime Compliance: Reducing Risks, Enhancing Efficiency
The global financial system is under siege from a wave of sophisticated financial crimes. Money laundering, with its estimated annual impact of $800 billion to $2 trillion, fraud losses exceeding $485.6 billion in 2023, cybercrime, and international financial manipulation threaten the integrity of the global financial system.
These crimes have a profound impact, undermining financial system stability, eroding public trust, and impacting government revenues.
Crucially, as retired Mexican politician Enrique Peña Nieto emphasised, "Money laundering is giving oxygen to organised crime,” fueling a cycle of further criminal activity.
Financial crimes reached a staggering $3.1 trillion globally in 2023, revealing how conventional compliance methods are falling short. In response, financial institutions are turning to advanced technologies – specifically RPA, AI, and ML – which together create intelligent automation (IA) systems to better combat these threats. This transformative defense mechanism represents a crucial shift in how the financial sector defends against criminal activity.
As financial institutions modernise their defenses, they are not just upgrading technology—they are building a more resilient financial system capable of protecting against both current and emerging criminal threats.
Key Implementation Areas
Effectively combating financial crime requires a synergistic approach, integrating emerging technologies across various domains which include
- :Proactive risk identification and transaction monitoring: RPA works alongside AI/ML to automate routine data collection and analysis tasks, while AI/ML empowers institutions to significantly enhance their risk identification capabilities. Together, these technologies fortify transaction monitoring systems for improved detection and flagging of suspicious patterns, reduce false positive alerts by minimising disruptions to legitimate customer activity, and provide explainable risk findings to enhance transparency.
- Streamlined investigations and KYC: IA platforms revolutionise investigative workflows by automating the Synthetic-aperture radar (SAR) generation process. RPA bots source data from various sources, and simplify interactions with customers and regulatory bodies. This automation also extends to Know Your Customer (KYC) processes that enable institutions to streamline customer onboarding and due diligence while complying with constantly changing regulations. These platforms seamlessly integrate with existing risk management systems, ensuring easy flow of information across all compliance functions.
- Adaptive regulatory compliance: As regulations continue to evolve, Generative AI plays a pivotal role in monitoring and summarising regulatory changes. While Generative AI analyzes and summarizes regulatory updates, RPA automates the implementation of required changes, enabling swift process adjustments and automating software updates. This adaptability is further enhanced by automated compliance testing, which continuously assesses control effectiveness, ensuring institutions uphold strong compliance standards while seamlessly adapting to new requirements.
Following an integrated approach enables financial institutions to create a comprehensive and dynamic compliance framework. This enhances their capability in the fight against financial crime, adds to operational efficiency, reduces costs, and further bolsters the risk management framework of the organisation.
The Automation Continuum
To effectively leverage emerging technologies, financial institutions can adopt a phased approach along an "Automation Continuum", progressing from basic automation to advanced cognitive systems.
At the foundation lies RPA, which automates repetitive manual tasks with low cost and rapid implementation. As organisations mature, they advance to AI/ML solutions that enhance decision-making by learning from historical data, significantly reducing false positives in monitoring systems. At the pinnacle sits Cognitive Automation, featuring advanced self-learning platforms that mimic human reasoning to uncover complex, emerging risks.
This graduated approach allows institutions to build vendor-agnostic solutions while systematically transitioning from basic automation to sophisticated AI capabilities, ensuring each step builds upon the previous one's success.
Key Drivers of Change
The financial services industry faces a complex and challenging operating environment. Regulatory scrutiny is intensifying, with supervisors demanding more sophisticated monitoring and reporting while maintaining high standards of effectiveness. Simultaneously, cost pressures are mounting as compliance departments grapple with growing operational demands while contending with limited resources.
Further complicating the picture is the emergence of new and sophisticated financial crimes. Trade-based money laundering, platform fraud facilitated by the rise of digital platforms, and the rapid growth of cryptocurrencies have created new avenues for illicit activities.
Adding to these challenges are innovative competitors (agile fintech startups to established technology giants), who are raising customer expectations by demonstrating the transformative power of technology-enabled compliance.
These converging forces have intensified the need for financial institutions to fast-track compliance transformation, adopting innovative solutions that drive efficiency, enhance effectiveness, and mitigate risk.
Critical Considerations
Success in implementing IA requires careful planning and execution. Organisations must develop a tailored automation strategy that aligns with their specific risk profile, operational model, and technological maturity.
Transparency is paramount – automated systems must provide clear visibility into decision-making processes and risk assessments. Maintaining robust audit trails becomes even more critical as automation increases, ensuring that all automated decisions and actions can be traced and validated.
Perhaps most importantly, institutions must carefully calibrate their technology adoption to match their risk tolerance, ensuring that innovation doesn't compromise risk management effectiveness.
The Strategic Imperative
In today's rapidly evolving threat landscape, financial institutions face a critical imperative: innovate or face disruption. As criminal activities become increasingly sophisticated, organisations must continuously evolve their technological capabilities to maintain effective defenses. By strategically implementing IA and embracing AI technologies, financial institutions can move to proactive financial crime compliance that anticipates and prevents emerging threats. This approach not only enhances risk mitigation and strengthens regulatory compliance but also improves customer experience, reduces operational costs, and provides a significant competitive advantage.
How can Infosys BPM help?
The financial services industry faces mounting regulatory pressure to enhance compliance across KYC, AML, and fraud prevention. This, coupled with evolving regulations, siloed systems, and resource constraints, presents significant challenges. Infosys BPM’s compliance practice BPM services offers end-to-end solutions, leveraging its domain expertise, cutting-edge technology, and strategic partnerships that enable financial institutions to navigate this complex landscape effectively.
